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Workshop
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Contrasting random and learned features in deep Bayesian linear regression
Jacob Zavatone-Veth · William Tong · Cengiz Pehlevan
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Poster
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Thu 9:00
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On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification
Sanyam Kapoor · Wesley Maddox · Pavel Izmailov · Andrew Wilson
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Poster
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Tue 14:00
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Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction
Dilip Arumugam · Satinder Singh
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Poster
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Thu 14:00
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Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces
Leonard Papenmeier · Luigi Nardi · Matthias Poloczek
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Poster
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Tue 9:00
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Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning
Dilip Arumugam · Benjamin Van Roy
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Poster
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Thu 14:00
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Bayesian Risk Markov Decision Processes
Yifan Lin · Yuxuan Ren · Enlu Zhou
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Poster
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Tue 9:00
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Laplacian Autoencoders for Learning Stochastic Representations
Marco Miani · Frederik Warburg · Pablo Moreno-Muñoz · Nicki Skafte · Søren Hauberg
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Workshop
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Bayesian Dynamic Causal Discovery
Alexander Tong · Lazar Atanackovic · Jason Hartford · Yoshua Bengio
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Workshop
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Variational Bayesian Inference and Learning for Continuous Switching Linear Dynamical Systems
Jack Goffinet · David Carlson
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Poster
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Wed 9:00
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Model-based Lifelong Reinforcement Learning with Bayesian Exploration
Haotian Fu · Shangqun Yu · Michael Littman · George Konidaris
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Workshop
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Fantasizing with Dual GPs in Bayesian Optimization and Active Learning
Paul Chang · Prakhar Verma · ST John · Victor Picheny · Henry Moss · Arno Solin
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Poster
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Tue 9:00
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Generalization Error Bounds on Deep Learning with Markov Datasets
Lan V. Truong
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